Create and Preprocess AML-ETO SO
TLusardi
11/02/2020
Set up libraries and directories
Read in data by run
Customize here as required per cellranger output naming convention * Note that "_" is reserved in Seurat (used as delimiter between an object key and a feature name) + https://github.com/satijalab/seurat/issues/3219
## 10X data contains more than one type and is being returned as a list containing matrices of each type.## [1] "Column order consistent - antibody and gene expression"
## [1] "***********************************************"
## [1] "CellRanger Output dmso: 33538 features in 2478 cells"
## [1] "Feature counts range 0 to 1643905"
## [1] "Features with 0 counts: 13356"
## [1] "Features with 1-3 counts: 3794"
## [1] "Cell feature counts range 500 to 107283"
## [1] "Cells with 500 counts: 1"
## [1] "CellRanger Antibody Output dmso: 8 features in 2478 cells"
## [1] "Antibody counts range 53493 to 712715"
## [1] "Antibody with 53493 counts: 1"
## [1] "Cell antibody counts range 34 to 367054"
## [1] "Cells with 34 counts: 1"
## [1] "dmso: 0 cells in ADT matrix that are not present in gene expression matrix"
## [1] "dmso: 0 cells in gene expression matrix that are not present in ADT matrix"## 10X data contains more than one type and is being returned as a list containing matrices of each type.## [1] "Column order consistent - antibody and gene expression"
## [1] "***********************************************"
## [1] "CellRanger Output ava: 33538 features in 4029 cells"
## [1] "Feature counts range 0 to 2103100"
## [1] "Features with 0 counts: 12871"
## [1] "Features with 1-3 counts: 3755"
## [1] "Cell feature counts range 500 to 80112"
## [1] "Cells with 500 counts: 5"
## [1] "CellRanger Antibody Output ava: 8 features in 4029 cells"
## [1] "Antibody counts range 65529 to 776274"
## [1] "Antibody with 65529 counts: 1"
## [1] "Cell antibody counts range 5 to 251337"
## [1] "Cells with 5 counts: 1"
## [1] "ava: 0 cells in ADT matrix that are not present in gene expression matrix"
## [1] "ava: 0 cells in gene expression matrix that are not present in ADT matrix"## 10X data contains more than one type and is being returned as a list containing matrices of each type.## [1] "Column order consistent - antibody and gene expression"
## [1] "***********************************************"
## [1] "CellRanger Output ory: 33538 features in 4212 cells"
## [1] "Feature counts range 0 to 2516846"
## [1] "Features with 0 counts: 12744"
## [1] "Features with 1-3 counts: 3692"
## [1] "Cell feature counts range 501 to 62086"
## [1] "Cells with 501 counts: 2"
## [1] "CellRanger Antibody Output ory: 8 features in 4212 cells"
## [1] "Antibody counts range 140493 to 715041"
## [1] "Antibody with 140493 counts: 1"
## [1] "Cell antibody counts range 1 to 160862"
## [1] "Cells with 1 counts: 1"
## [1] "ory: 0 cells in ADT matrix that are not present in gene expression matrix"
## [1] "ory: 0 cells in gene expression matrix that are not present in ADT matrix"## 10X data contains more than one type and is being returned as a list containing matrices of each type.## [1] "Column order consistent - antibody and gene expression"
## [1] "***********************************************"
## [1] "CellRanger Output combo: 33538 features in 2349 cells"
## [1] "Feature counts range 0 to 1401365"
## [1] "Features with 0 counts: 13633"
## [1] "Features with 1-3 counts: 3719"
## [1] "Cell feature counts range 502 to 66262"
## [1] "Cells with 502 counts: 1"
## [1] "CellRanger Antibody Output combo: 8 features in 2349 cells"
## [1] "Antibody counts range 129232 to 509767"
## [1] "Antibody with 129232 counts: 1"
## [1] "Cell antibody counts range 11 to 172768"
## [1] "Cells with 11 counts: 1"
## [1] "combo: 0 cells in ADT matrix that are not present in gene expression matrix"
## [1] "combo: 0 cells in gene expression matrix that are not present in ADT matrix"Take a quick look at ADT concordance
## [1] "ab-CD10: MME RNA present in fewer than 3 cells in dmso object"
## [1] "ab-CD90: THY1 RNA present in fewer than 3 cells in dmso object"
## Warning in xy.coords(x, y, xlabel, ylabel, log): 1 y value <= 0 omitted from
## logarithmic plot
## Warning in xy.coords(x, y, xlabel, ylabel, log): 1 y value <= 0 omitted from
## logarithmic plot
## [1] "ab-CD10: MME RNA present in fewer than 3 cells in ava object"
## [1] "ab-CD90: THY1 RNA present in fewer than 3 cells in ava object"## Warning in xy.coords(x, y, xlabel, ylabel, log): 8 y values <= 0 omitted from
## logarithmic plot
## Warning in xy.coords(x, y, xlabel, ylabel, log): 1 y value <= 0 omitted from
## logarithmic plot
## Warning in xy.coords(x, y, xlabel, ylabel, log): 1 y value <= 0 omitted from
## logarithmic plot
## Warning in xy.coords(x, y, xlabel, ylabel, log): 1 y value <= 0 omitted from
## logarithmic plot
## Warning in xy.coords(x, y, xlabel, ylabel, log): 2 y values <= 0 omitted from
## logarithmic plot
## [1] "ab-CD10: MME RNA present in fewer than 3 cells in ory object"
## [1] "ab-CD90: THY1 RNA present in fewer than 3 cells in ory object"## Warning in xy.coords(x, y, xlabel, ylabel, log): 2 y values <= 0 omitted from
## logarithmic plot
## Warning in xy.coords(x, y, xlabel, ylabel, log): 1 y value <= 0 omitted from
## logarithmic plot
## Warning in xy.coords(x, y, xlabel, ylabel, log): 1 y value <= 0 omitted from
## logarithmic plot
## Warning in xy.coords(x, y, xlabel, ylabel, log): 1 y value <= 0 omitted from
## logarithmic plot
## Warning in xy.coords(x, y, xlabel, ylabel, log): 3 y values <= 0 omitted from
## logarithmic plot
## [1] "ab-CD10: MME RNA present in fewer than 3 cells in combo object"
## [1] "ab-CD90: THY1 RNA present in fewer than 3 cells in combo object"## Warning in xy.coords(x, y, xlabel, ylabel, log): 11 y values <= 0 omitted from
## logarithmic plot
## Warning in xy.coords(x, y, xlabel, ylabel, log): 1 y value <= 0 omitted from
## logarithmic plot
## Warning in xy.coords(x, y, xlabel, ylabel, log): 7 y values <= 0 omitted from
## logarithmic plot
Summary Plots
Summarize data to make filtering decisions
Preprocess Runs
Based on summary plots, filter out cells with excess mitochondrial RNA, low/high counts Assign Cell Cycle Scores
- Note that the cell cycle scores are influenced by the population of cells (before and after filtering give different results)
- A casual look showed that all of the scores are different, differences are all different (so it’s not just a shift), and a small number of Phase assignments are different (~10% from an n=1 off the cuff analysis))
## [1] "dmso: Filter cells > 12% mitochondria: 563/2341 (24.0%)"
## [1] "dmso: Filter cells with 200 > nCount > 25000: 122/2341 (5.2%)"
## [1] "Filtered dmso: 1657 cells, 16953 features"## Warning: The following features are not present in the object: PIMREG, not
## searching for symbol synonyms## [1] "ava: Filter cells > 12% mitochondria: 996/3829 (26.0%)"
## [1] "ava: Filter cells with 200 > nCount > 25000: 79/3829 (2.1%)"
## [1] "Filtered ava: 2754 cells, 17515 features"
## [1] "ory: Filter cells > 12% mitochondria: 542/4070 (13.3%)"
## [1] "ory: Filter cells with 200 > nCount > 25000: 124/4070 (3.0%)"
## [1] "Filtered ory: 3404 cells, 17700 features"
## [1] "combo: Filter cells > 12% mitochondria: 263/2292 (11.5%)"
## [1] "combo: Filter cells with 200 > nCount > 25000: 156/2292 (6.8%)"
## [1] "Filtered combo: 1873 cells, 16787 features"## Warning: The following features are not present in the object: RAD51, not
## searching for symbol synonymsNormalize & Scale
Quick look to assess regression needs
## Centering and scaling data matrix## PC_ 1
## Positive: FCER1G, CYBB, CD14, NCF2, SLC7A11, CTSB, C5AR1, CTSL, NRP1, MAFB
## EMP1, CLEC5A, S100A9, CCR1, DUSP6, CD300E, FTL, ANXA5, NPC2, PLAUR
## CD93, ATP13A3, SIRPA, ITGAX, RBM47, TIMP1, SLC16A3, RAB31, CSF1R, CXCL8
## Negative: RPS18, ITM2A, GBP4, EGFL7, SEPT6, SOX4, STMN1, CXCR4, GBP2, GYPC
## LYSMD2, NCOA7, SERPINB1, FAM117A, SLC27A2, RHEX, HMGN3, SPN, ARHGEF6, PDCD4
## PTMA, SMYD3, MYB, APEX1, ERG, IRF1, MIS18BP1, DDB2, ABCC4, ANGPT1
## PC_ 2
## Positive: SERPINB1, HLA-DRA, GSN, CELF2, H2AFY, HLA-DRB1, DBI, LGALS1, CD74, HLA-DRB5
## TFPI, ITM2A, GOLIM4, EGFL7, SEPT11, SLC27A2, SPN, NEAT1, HLA-DMA, TXN
## ARHGEF6, CD9, GBP4, SOX4, VMP1, CDK6, ETS2, PYGL, NCOA7, ORAI2
## Negative: CD3G, CD3E, CD2, CD3D, TRBC1, SYNE2, CCL5, CD81, SAMD3, CD247
## GIMAP4, LCK, SPOCK2, RORA, FYN, GZMH, NKG7, TRAC, GZMB, LSP1
## BTG1, GZMM, IKZF3, C12orf75, LINC01871, GIMAP7, CLEC2D, CLIC3, KLRD1, CD8A
## PC_ 3
## Positive: NCF1, ADAM28, CFP, GPR183, DAPP1, FCGR2B, MARCKSL1, ALOX5, CSF2RA, FAM129A
## GLIPR1, PSTPIP2, LST1, RASA4, CEBPD, ITGB2, PPA1, HLA-DQB1, LYZ, CLEC10A
## NAV1, MARCH1, AC064805.1, SLC38A1, YWHAH, HLA-DRB1, PALLD, PTGIR, IGSF6, PKIB
## Negative: GCSAML, SLC27A2, CXCL5, CPA3, GATA2, CD163, CYTOR, MSR1, RHEX, MT2A
## RAB33A, CXCL3, CXCL1, NPL, HS3ST1, RNASE1, IKZF2, IQGAP2, FAM117A, CXCL2
## ANGPT1, PLIN2, SPTBN1, FAM171A1, NTRK1, ZFP36L1, CTSL, HACD1, MERTK, ZBTB16
## PC_ 4
## Positive: CD79A, IGHM, MS4A1, PLCG2, CD79B, TNFRSF13C, BANK1, RALGPS2, LINC02397, IGHD
## TCL1A, IGKC, AFF3, VPREB3, PLEKHG1, POU2AF1, SPIB, C16orf74, LTB, LINC00926
## RAB30, CCR7, FAM30A, IGLC3, AC025164.1, BLNK, IGLC2, BASP1, FAM177B, SESN3
## Negative: CCL5, CST7, NKG7, IL32, GZMH, SAMD3, RARRES3, CD3G, TMSB4X, GZMB
## OASL, CD2, CD3D, LY6E, SLFN5, CD3E, ISG15, C12orf75, ANXA1, C1orf21
## GNLY, SH2D2A, KLRD1, STAT1, KLRG1, CXCR3, GZMM, CD8B, SPN, LINC01871
## PC_ 5
## Positive: PYCARD, LAT2, CLEC11A, LST1, NME1, TPSAB1, DDX21, GAPT, LMO4, EIF4EBP1
## AL034397.3, ALOX5AP, PRSS57, NFE2, S100A8, GMPR, LYZ, CEBPA, S100A4, CPA3
## MYC, RNASE2, ITGB2, RAB37, CSTA, IGSF6, CD300LF, XBP1, CST3, GDF11
## Negative: CCR7, TNFSF4, NRP2, PALLD, CYTIP, PDE4B, TSC22D1, CD83, NEAT1, DUSP5
## DAPP1, MS4A7, CXCR4, C1QTNF1, MTSS1, ADA, CDKN1A, TNFRSF4, BHLHE41, FAM107B
## KLF6, AR, ARMC9, IL10RA, KYNU, SIPA1L1, ITGB8, SSH1, ISG20, EBI3## Regressing out percent.mt## Centering and scaling data matrix## PC_ 1
## Positive: FCER1G, CYBB, CD14, NCF2, SLC7A11, CTSB, C5AR1, NRP1, CTSL, MAFB
## CLEC5A, EMP1, S100A9, CCR1, DUSP6, CD300E, FTL, ANXA5, NPC2, PLAUR
## CD93, ATP13A3, SIRPA, ITGAX, TIMP1, RBM47, SLC16A3, CSF1R, RAB31, CXCL8
## Negative: RPS18, ITM2A, GBP4, EGFL7, SEPT6, SOX4, STMN1, CXCR4, GBP2, GYPC
## LYSMD2, NCOA7, SERPINB1, SLC27A2, FAM117A, SPN, RHEX, ARHGEF6, HMGN3, PDCD4
## SMYD3, PTMA, MYB, APEX1, ERG, IRF1, MIS18BP1, DDB2, ABCC4, ANGPT1
## PC_ 2
## Positive: SERPINB1, HLA-DRA, CELF2, H2AFY, LGALS1, GSN, HLA-DRB1, DBI, TFPI, ITM2A
## HLA-DRB5, CD74, EGFL7, GOLIM4, TXN, SLC27A2, SEPT11, HLA-DMA, PKM, SOX4
## ARHGEF6, GBP4, CDK6, SPN, PYGL, RHEX, ETS2, NCOA7, SSBP2, FSCN1
## Negative: CD3G, CD3E, CD2, CD3D, TRBC1, CCL5, SYNE2, CD81, SAMD3, CD247
## LCK, GIMAP4, SPOCK2, RORA, GZMH, GZMB, GZMM, NKG7, FYN, TRAC
## LSP1, C12orf75, IKZF3, BTG1, LINC01871, CLIC3, KLRD1, GIMAP7, CD8A, CLEC2D
## PC_ 3
## Positive: NCF1, ADAM28, CFP, GPR183, DAPP1, FCGR2B, MARCKSL1, CSF2RA, FAM129A, ALOX5
## GLIPR1, PSTPIP2, LST1, RASA4, CEBPD, HLA-DQB1, ITGB2, PPA1, LYZ, NAV1
## CLEC10A, MARCH1, HLA-DRB1, SLC38A1, AC064805.1, YWHAH, PTGIR, PALLD, IGSF6, HLA-DQA1
## Negative: GCSAML, SLC27A2, CPA3, GATA2, CXCL5, CYTOR, CD163, RHEX, MSR1, RAB33A
## MT2A, CXCL3, CXCL1, NPL, IKZF2, IQGAP2, FAM117A, ANGPT1, HS3ST1, CXCL2
## SPTBN1, RNASE1, PLIN2, FAM171A1, NTRK1, HACD1, CTSL, ZFP36L1, MERTK, ZBTB16
## PC_ 4
## Positive: CD79A, IGHM, MS4A1, PLCG2, CD79B, TNFRSF13C, BANK1, RALGPS2, LINC02397, IGHD
## IGKC, TCL1A, CCR7, AFF3, VPREB3, SPIB, PLEKHG1, POU2AF1, LTB, C16orf74
## RAB30, LINC00926, CD83, IGLC3, BASP1, AC025164.1, FAM30A, SESN3, BLNK, IGLC2
## Negative: TMSB4X, NKG7, CCL5, CST7, RARRES3, GZMH, SAMD3, IL32, CD3G, GZMB
## OASL, CD3D, ISG15, CD2, LY6E, SPN, C12orf75, STAT1, SLFN5, CD3E
## DBI, ANXA1, C1orf21, SH2D2A, GNLY, SRGN, KLRD1, IQGAP2, IFI6, KLRG1
## PC_ 5
## Positive: NRP2, TNFSF4, PALLD, CCR7, PDE4B, CYTIP, MS4A7, CXCR4, NEAT1, ADA
## TNFRSF4, TSC22D1, CDKN1A, DUSP5, DAPP1, MTSS1, C1QTNF1, KLF6, FAM107B, CD83
## AR, BHLHE41, EBI3, SSH1, ARMC9, SIPA1L1, PEAK1, ISG20, RFTN1, IL10RA
## Negative: PYCARD, LAT2, TPSAB1, LST1, GAPT, CLEC11A, NME1, S100A8, NFE2, AL034397.3
## LMO4, DDX21, LYZ, PRSS57, ALOX5AP, EIF4EBP1, GMPR, RNASE2, MYC, CEBPA
## S100A9, EGR1, CPA3, CD300LF, RAB37, CSTA, ITGB2, AC020656.1, IGSF6, CCNA1
## Regressing out Phase## Centering and scaling data matrix## PC_ 1
## Positive: FCER1G, CYBB, CD14, NCF2, SLC7A11, C5AR1, CTSB, CTSL, MAFB, NRP1
## EMP1, CLEC5A, CCR1, S100A9, CD300E, DUSP6, CD93, FTL, NPC2, ANXA5
## PLAUR, ATP13A3, ITGAX, SIRPA, RBM47, RAB31, SLC16A3, TIMP1, CXCL8, TGFBI
## Negative: RPS18, ITM2A, GBP4, SEPT6, EGFL7, SOX4, GBP2, STMN1, CXCR4, NCOA7
## LYSMD2, GYPC, SERPINB1, SLC27A2, FAM117A, SPN, HMGN3, ARHGEF6, RHEX, SMYD3
## PDCD4, MYB, PTMA, ERG, APEX1, DDB2, IRF1, ABCC4, MIS18BP1, ANGPT1
## PC_ 2
## Positive: SERPINB1, HLA-DRA, GSN, CELF2, H2AFY, LGALS1, HLA-DRB1, DBI, CD74, HLA-DRB5
## ITM2A, EGFL7, TFPI, GOLIM4, SEPT11, NEAT1, SOX4, SLC27A2, SPN, TXN
## VMP1, ARHGEF6, HLA-DMA, PYGL, CD9, ETS2, RHEX, GBP4, CDK6, PKM
## Negative: CD3G, CD3E, CD2, CD3D, TRBC1, SYNE2, CCL5, CD81, SAMD3, CD247
## GIMAP4, LCK, SPOCK2, RORA, FYN, NKG7, GZMH, GZMB, TRAC, IKZF3
## LSP1, GZMM, BTG1, C12orf75, CLEC2D, GIMAP7, LINC01871, CLIC3, KLRD1, CD8A
## PC_ 3
## Positive: NCF1, ADAM28, CFP, GPR183, FCGR2B, DAPP1, MARCKSL1, CSF2RA, ALOX5, PSTPIP2
## LST1, GLIPR1, FAM129A, RASA4, ITGB2, CEBPD, LYZ, PPA1, HLA-DQB1, CLEC10A
## MARCH1, NAV1, IGSF6, AC064805.1, YWHAH, HLA-DRB1, SLC38A1, TYMP, PTGIR, PALLD
## Negative: GCSAML, SLC27A2, CD163, CXCL5, GATA2, CPA3, CYTOR, MSR1, RHEX, CXCL3
## RAB33A, MT2A, CXCL1, NPL, CXCL2, HS3ST1, RNASE1, IKZF2, FAM117A, ANGPT1
## IQGAP2, SPTBN1, CTSL, ZFP36L1, PLIN2, FAM171A1, NTRK1, MERTK, HACD1, PPBP
## PC_ 4
## Positive: CD79A, IGHM, PLCG2, MS4A1, CD79B, TNFRSF13C, BANK1, RALGPS2, LINC02397, IGHD
## IGKC, TCL1A, AFF3, VPREB3, SPIB, PLEKHG1, POU2AF1, CCR7, LTB, C16orf74
## RAB30, LINC00926, IGLC3, FAM30A, AC025164.1, CD83, BASP1, IGLC2, FAM177B, SESN3
## Negative: CCL5, NKG7, TMSB4X, CST7, RARRES3, IL32, GZMH, SAMD3, CD3G, CD3D
## OASL, GZMB, CD2, LY6E, ISG15, CD3E, C12orf75, SLFN5, STAT1, C1orf21
## ANXA1, GNLY, SPN, KLRD1, SH2D2A, KLRG1, IFI6, GZMM, CXCR3, CD8B
## PC_ 5
## Positive: TNFSF4, NRP2, PALLD, CCR7, MS4A7, PDE4B, NEAT1, TSC22D1, ADA, DUSP5
## C1QTNF1, DAPP1, MTSS1, BHLHE41, CYTIP, KLF6, CXCR4, CDKN1A, CD83, TNFRSF4
## AR, ITGB8, ARMC9, FAM107B, IL10RA, SSH1, KYNU, ISG20, EBI3, FAM49A
## Negative: PYCARD, LAT2, NME1, LST1, DDX21, TPSAB1, CLEC11A, LMO4, EIF4EBP1, S100A8
## GAPT, ALOX5AP, CPA3, LYZ, NFE2, GMPR, PRSS57, S100A4, CSTA, GCSAML
## AL034397.3, CEBPA, IGSF6, S100A9, GDF11, CCNA1, ITGB2, EGR1, MYC, RNASE2
## Regressing out Phase, percent.mt## Centering and scaling data matrix## PC_ 1
## Positive: FCER1G, CYBB, CD14, NCF2, SLC7A11, CTSB, C5AR1, CTSL, NRP1, MAFB
## CLEC5A, EMP1, CCR1, S100A9, DUSP6, CD300E, CD93, FTL, NPC2, ANXA5
## PLAUR, ATP13A3, SIRPA, ITGAX, RBM47, RAB31, TIMP1, SLC16A3, CSF1R, TGFBI
## Negative: RPS18, ITM2A, GBP4, SEPT6, EGFL7, SOX4, GBP2, STMN1, CXCR4, NCOA7
## LYSMD2, GYPC, SERPINB1, SLC27A2, FAM117A, SPN, HMGN3, ARHGEF6, RHEX, PDCD4
## SMYD3, MYB, PTMA, ERG, APEX1, DDB2, IRF1, ABCC4, MIS18BP1, ANGPT1
## PC_ 2
## Positive: SERPINB1, HLA-DRA, CELF2, H2AFY, LGALS1, GSN, HLA-DRB1, DBI, ITM2A, EGFL7
## TFPI, HLA-DRB5, TXN, GOLIM4, CD74, SOX4, SLC27A2, PKM, ARHGEF6, SEPT11
## HLA-DMA, RHEX, CDK6, GBP4, SPN, PYGL, ETS2, MYB, ERG, VMP1
## Negative: CD3G, CD3E, CD2, CD3D, TRBC1, CCL5, SYNE2, CD81, SAMD3, CD247
## LCK, GIMAP4, SPOCK2, RORA, GZMB, GZMH, NKG7, FYN, GZMM, TRAC
## LSP1, IKZF3, C12orf75, BTG1, LINC01871, CLIC3, KLRD1, CD8A, CLEC2D, GIMAP7
## PC_ 3
## Positive: NCF1, ADAM28, CFP, GPR183, DAPP1, FCGR2B, MARCKSL1, CSF2RA, ALOX5, FAM129A
## GLIPR1, PSTPIP2, LST1, RASA4, ITGB2, CEBPD, LYZ, HLA-DQB1, PPA1, CLEC10A
## NAV1, MARCH1, HLA-DRB1, AC064805.1, IGSF6, YWHAH, SLC38A1, PTGIR, PALLD, TYMP
## Negative: GCSAML, SLC27A2, CPA3, GATA2, CD163, CYTOR, CXCL5, MSR1, RHEX, CXCL3
## RAB33A, MT2A, CXCL1, NPL, IKZF2, FAM117A, CXCL2, IQGAP2, ANGPT1, HS3ST1
## RNASE1, SPTBN1, FAM171A1, CTSL, PLIN2, ZFP36L1, NTRK1, HACD1, MERTK, ZBTB16
## PC_ 4
## Positive: CD79A, IGHM, PLCG2, MS4A1, CD79B, TNFRSF13C, BANK1, RALGPS2, IGKC, LINC02397
## IGHD, TCL1A, CCR7, AFF3, VPREB3, SPIB, PLEKHG1, POU2AF1, LTB, CD83
## C16orf74, RAB30, LINC00926, BASP1, IGLC3, AC025164.1, SESN3, FAM30A, IGLC2, KYNU
## Negative: TMSB4X, NKG7, CCL5, RARRES3, CST7, GZMH, SAMD3, CD3D, CD3G, IL32
## OASL, GZMB, ISG15, SPN, LY6E, CD2, STAT1, C12orf75, DBI, CD3E
## SLFN5, C1orf21, ANXA1, SRGN, IQGAP2, GNLY, SH2D2A, PYCARD, IFI6, KLRD1
## PC_ 5
## Positive: PALLD, NRP2, TNFSF4, ADA, MS4A7, PDE4B, MTSS1, NEAT1, CCR7, BHLHE41
## KLF6, DUSP5, C1QTNF1, TSC22D1, TNFRSF4, DAPP1, CXCR4, CDKN1A, CYTIP, AR
## EBI3, SSH1, FAM107B, RFTN1, ITGB8, CD83, ARMC9, ISG20, IL10RA, SIPA1L1
## Negative: PYCARD, LAT2, LST1, NME1, TPSAB1, S100A8, DDX21, GAPT, CPA3, LYZ
## EIF4EBP1, LMO4, ALOX5AP, CLEC11A, NFE2, EGR1, S100A9, CSTA, AL034397.3, GMPR
## PRSS57, RNASE2, MYC, CEBPA, CCNA1, ITGB2, GCSAML, CD300LF, IGSF6, RAB37
## Regressing out CC.Difference## Centering and scaling data matrix## PC_ 1
## Positive: FCER1G, CYBB, CD14, NCF2, SLC7A11, CTSB, C5AR1, CTSL, MAFB, NRP1
## EMP1, S100A9, CLEC5A, CCR1, CD300E, DUSP6, ANXA5, FTL, NPC2, CD93
## PLAUR, ATP13A3, SIRPA, ITGAX, RBM47, SLC16A3, TIMP1, RAB31, CXCL8, CSF1R
## Negative: RPS18, ITM2A, GBP4, EGFL7, SEPT6, SOX4, STMN1, GYPC, CXCR4, GBP2
## SERPINB1, LYSMD2, NCOA7, SLC27A2, FAM117A, ARHGEF6, SPN, HMGN3, RHEX, SMYD3
## PTMA, PDCD4, APEX1, MYB, ERG, IRF1, DDB2, ABCC4, MIS18BP1, ANGPT1
## PC_ 2
## Positive: SERPINB1, HLA-DRA, GSN, CELF2, H2AFY, LGALS1, HLA-DRB1, DBI, TFPI, CD74
## ITM2A, HLA-DRB5, EGFL7, GOLIM4, SEPT11, NEAT1, SPN, VMP1, TXN, SLC27A2
## CD9, SOX4, ETS2, GBP4, HLA-DMA, ARHGEF6, PYGL, RHEX, NCOA7, CDK6
## Negative: CD3G, CD3E, CD2, CD3D, TRBC1, SYNE2, CCL5, CD81, SAMD3, CD247
## GIMAP4, LCK, SPOCK2, RORA, FYN, GZMH, TRAC, NKG7, GZMB, LSP1
## IKZF3, GZMM, BTG1, C12orf75, LINC01871, CLEC2D, GIMAP7, CLIC3, KLRD1, CD8A
## PC_ 3
## Positive: NCF1, ADAM28, CFP, GPR183, DAPP1, FCGR2B, MARCKSL1, CSF2RA, ALOX5, PSTPIP2
## FAM129A, GLIPR1, LST1, RASA4, CEBPD, ITGB2, PPA1, LYZ, HLA-DQB1, CLEC10A
## NAV1, MARCH1, AC064805.1, YWHAH, SLC38A1, HLA-DRB1, IGSF6, PALLD, PTGIR, PKIB
## Negative: GCSAML, SLC27A2, CXCL5, CD163, GATA2, CPA3, CYTOR, MSR1, RHEX, CXCL3
## CXCL1, RAB33A, MT2A, NPL, HS3ST1, CXCL2, RNASE1, FAM117A, IKZF2, IQGAP2
## ANGPT1, PLIN2, SPTBN1, FAM171A1, CTSL, NTRK1, ZFP36L1, MERTK, HACD1, PPBP
## PC_ 4
## Positive: CD79A, PLCG2, IGHM, MS4A1, CD79B, TNFRSF13C, BANK1, RALGPS2, LINC02397, IGHD
## TCL1A, IGKC, AFF3, VPREB3, CCR7, SPIB, PLEKHG1, POU2AF1, LTB, C16orf74
## RAB30, LINC00926, IGLC3, FAM30A, AC025164.1, CD83, BASP1, SESN3, IGLC2, FAM177B
## Negative: CCL5, NKG7, CST7, TMSB4X, RARRES3, SAMD3, GZMH, CD3G, IL32, CD3D
## GZMB, CD2, OASL, C12orf75, CD3E, LY6E, ISG15, SLFN5, C1orf21, SH2D2A
## GNLY, STAT1, KLRD1, SPN, KLRG1, CD8B, IFI6, GZMM, CXCR3, TRBC1
## PC_ 5
## Positive: TNFSF4, PALLD, NRP2, NEAT1, PDE4B, MS4A7, CYTIP, CCR7, TSC22D1, ADA
## CXCR4, MTSS1, DUSP5, C1QTNF1, KLF6, BHLHE41, DAPP1, CDKN1A, TNFRSF4, AR
## FAM107B, IL10RA, SSH1, KYNU, ARMC9, EBI3, CD83, ISG20, ITGB8, RFTN1
## Negative: PYCARD, NME1, LAT2, DDX21, LST1, TPSAB1, EIF4EBP1, CLEC11A, MYC, LMO4
## HSPE1, NFE2, PRSS57, GAPT, S100A8, CSTA, GMPR, LYZ, ALOX5AP, CEBPA
## CPA3, AL034397.3, RNASE2, RPL22L1, XBP1, CCNA1, EGR1, MRPL12, CD300LF, RAB37
## Regressing out CC.Difference, percent.mt## Centering and scaling data matrix## PC_ 1
## Positive: FCER1G, CYBB, CD14, NCF2, SLC7A11, CTSB, C5AR1, NRP1, CTSL, MAFB
## CLEC5A, EMP1, S100A9, CCR1, CD300E, DUSP6, ANXA5, FTL, NPC2, PLAUR
## CD93, ATP13A3, SIRPA, ITGAX, RBM47, SLC16A3, TIMP1, CSF1R, RAB31, CXCL8
## Negative: RPS18, ITM2A, GBP4, EGFL7, SEPT6, SOX4, STMN1, GYPC, CXCR4, GBP2
## SERPINB1, LYSMD2, NCOA7, SLC27A2, FAM117A, SPN, ARHGEF6, HMGN3, RHEX, SMYD3
## PTMA, PDCD4, APEX1, MYB, ERG, IRF1, DDB2, ABCC4, MIS18BP1, ANGPT1
## PC_ 2
## Positive: SERPINB1, HLA-DRA, CELF2, H2AFY, LGALS1, GSN, HLA-DRB1, DBI, ITM2A, TFPI
## EGFL7, TXN, HLA-DRB5, GOLIM4, CD74, PKM, SOX4, SLC27A2, SEPT11, HLA-DMA
## RHEX, GBP4, ARHGEF6, ETS2, PYGL, SPN, CDK6, VMP1, FSCN1, ERG
## Negative: CD3G, CD3E, CD2, CD3D, TRBC1, SYNE2, CCL5, CD81, SAMD3, CD247
## LCK, GIMAP4, SPOCK2, RORA, GZMH, GZMB, FYN, GZMM, NKG7, TRAC
## LSP1, C12orf75, IKZF3, LINC01871, CLIC3, BTG1, KLRD1, CLEC2D, GIMAP7, CD8A
## PC_ 3
## Positive: NCF1, ADAM28, CFP, GPR183, DAPP1, FCGR2B, MARCKSL1, CSF2RA, FAM129A, ALOX5
## GLIPR1, PSTPIP2, LST1, RASA4, CEBPD, ITGB2, HLA-DQB1, PPA1, LYZ, NAV1
## CLEC10A, MARCH1, HLA-DRB1, SLC38A1, YWHAH, AC064805.1, PTGIR, PALLD, IGSF6, HLA-DQA1
## Negative: GCSAML, SLC27A2, CPA3, GATA2, CXCL5, CD163, CYTOR, RHEX, MSR1, RAB33A
## CXCL3, MT2A, CXCL1, NPL, IKZF2, FAM117A, IQGAP2, ANGPT1, HS3ST1, CXCL2
## RNASE1, PLIN2, SPTBN1, FAM171A1, CTSL, NTRK1, HACD1, ZFP36L1, MERTK, ZBTB16
## PC_ 4
## Positive: CD79A, IGHM, PLCG2, MS4A1, CD79B, TNFRSF13C, BANK1, RALGPS2, IGKC, CCR7
## LINC02397, IGHD, TCL1A, AFF3, VPREB3, SPIB, PLEKHG1, POU2AF1, LTB, CD83
## C16orf74, RAB30, LINC00926, KYNU, TSC22D1, BASP1, SAT1, AC025164.1, IGLC3, NEAT1
## Negative: TMSB4X, NKG7, CCL5, CST7, RARRES3, GZMH, SAMD3, CD3D, CD3G, GZMB
## CD2, IL32, OASL, ISG15, LY6E, C12orf75, SPN, CD3E, ASPM, STAT1
## SRM, DBI, SH2D2A, SLFN5, C1orf21, GNLY, PYCARD, IFI6, IQGAP2, ITGA4
## PC_ 5
## Positive: PYCARD, LAT2, NME1, DDX21, LST1, TPSAB1, EIF4EBP1, MYC, CLEC11A, GAPT
## NFE2, S100A8, LYZ, LMO4, PRSS57, AL034397.3, EGR1, CEBPA, HSPE1, RNASE2
## GMPR, CPA3, ALOX5AP, CSTA, S100A9, CCNA1, CD300LF, ASNS, RAB37, XBP1
## Negative: PALLD, TNFSF4, NRP2, MS4A7, PDE4B, ADA, NEAT1, MTSS1, CYTIP, CXCR4
## TNFRSF4, CDKN1A, KLF6, TSC22D1, DUSP5, C1QTNF1, BHLHE41, DAPP1, AR, CCR7
## FAM107B, SSH1, EBI3, PTMS, IL10RA, RFTN1, PEAK1, F2RL3, ARMC9, SIPA1L1
Assign Cell-Cycle Scores
So - filter first, then assign cell cycle scores
## Picking joint bandwidth of 0.362## Picking joint bandwidth of 0.113## Picking joint bandwidth of 0.775## Picking joint bandwidth of 0.506
## [1] "Sum the counts in s-phase genes across 1657 cells"
## CLSPN NASP USP1 DTL EXO1 RRM2 MSH2 POLR1B
## 75 2198 815 19 5 14 244 162
## MCM6 CDCA7 SLBP CENPU MRPL36 GMNN CASP8AP2 RFC2
## 178 126 1207 109 948 283 556 387
## MCM7 POLA1 MCM4 CCNE2 DSCC1 ATAD2 RRM1 E2F8
## 413 147 140 239 24 321 363 9
## FEN1 POLD3 HELLS RAD51AP1 PRIM1 UNG UBR7 RAD51
## 139 492 214 55 113 76 212 2
## WDR76 TIPIN BLM GINS2 CDC6 TYMS PCNA UHRF1
## 120 173 233 32 22 142 471 50
## CDC45 MCM5 CHAF1B
## 6 440 11
## [1] "Sum the counts in g2m-phase genes across 1657 cells"
## CDCA8 CDC20 KIF2C PSRC1 ANP32E CKS1B NUF2 NEK2 CENPF LBR
## 42 32 25 5 1319 319 30 10 193 2278
## CENPA BUB1 CKAP2L HJURP SMC4 ECT2 TACC3 CENPE HMGB2 CDC25C
## 8 53 28 17 1360 139 588 54 2070 7
## HMMR TTK ANLN CDCA2 CKS2 TUBB4B CKAP5 CDK1 KIF20B KIF11
## 55 16 26 21 465 5430 647 28 367 61
## MKI67 NCAPD2 CDCA3 CBX5 TMPO GAS2L3 CKAP2 G2E3 DLGAP5 NUSAP1
## 51 320 14 841 1860 173 635 618 25 149
## CCNB2 KIF23 CTCF AURKB TOP2A JPT1 BIRC5 NDC80 TPX2 UBE2C
## 69 130 1446 19 171 3870 24 36 92 38
## AURKA RANGAP1 GTSE1
## 201 337 32## Picking joint bandwidth of 0.316## Picking joint bandwidth of 0.194## Picking joint bandwidth of 0.931## Picking joint bandwidth of 0.539
## [1] "Sum the counts in s-phase genes across 2754 cells"
## CLSPN NASP USP1 DTL EXO1 RRM2 MSH2 POLR1B
## 116 3152 1279 58 12 26 353 224
## MCM6 CDCA7 SLBP CENPU MRPL36 GMNN CASP8AP2 RFC2
## 264 179 1713 191 1269 414 770 478
## MCM7 POLA1 MCM4 CCNE2 DSCC1 ATAD2 RRM1 E2F8
## 593 195 260 343 40 445 537 6
## FEN1 POLD3 HELLS RAD51AP1 PRIM1 UNG UBR7 RAD51
## 210 746 276 91 156 105 317 3
## WDR76 TIPIN BLM GINS2 CDC6 TYMS PCNA UHRF1
## 175 268 312 86 29 208 634 75
## CDC45 MCM5 CHAF1B
## 20 691 23
## [1] "Sum the counts in g2m-phase genes across 2754 cells"
## CDCA8 CDC20 KIF2C PSRC1 ANP32E CKS1B NUF2 NEK2 CENPF LBR
## 65 61 44 14 1925 492 61 23 437 3344
## CENPA BUB1 CKAP2L HJURP SMC4 ECT2 TACC3 CENPE HMGB2 CDC25C
## 16 92 43 45 1960 209 811 130 3123 11
## HMMR TTK ANLN CDCA2 CKS2 TUBB4B CKAP5 CDK1 KIF20B KIF11
## 108 39 38 13 617 7680 962 92 627 116
## MKI67 NCAPD2 CDCA3 CBX5 TMPO GAS2L3 CKAP2 G2E3 DLGAP5 NUSAP1
## 147 516 15 1286 2626 242 914 905 55 338
## CCNB2 KIF23 CTCF PIMREG AURKB TOP2A JPT1 BIRC5 NDC80 TPX2
## 105 187 2253 5 39 369 5714 107 74 167
## UBE2C AURKA RANGAP1 GTSE1
## 100 360 451 69## Picking joint bandwidth of 0.355## Picking joint bandwidth of 0.177## Picking joint bandwidth of 0.761## Picking joint bandwidth of 0.618
## [1] "Sum the counts in s-phase genes across 3404 cells"
## CLSPN NASP USP1 DTL EXO1 RRM2 MSH2 POLR1B
## 152 3912 1398 52 13 44 365 313
## MCM6 CDCA7 SLBP CENPU MRPL36 GMNN CASP8AP2 RFC2
## 352 221 2112 208 1839 483 922 640
## MCM7 POLA1 MCM4 CCNE2 DSCC1 ATAD2 RRM1 E2F8
## 737 244 245 510 39 628 563 16
## FEN1 POLD3 HELLS RAD51AP1 PRIM1 UNG UBR7 RAD51
## 226 1052 388 137 186 139 389 3
## WDR76 TIPIN BLM GINS2 CDC6 TYMS PCNA UHRF1
## 218 345 370 87 47 335 779 88
## CDC45 MCM5 CHAF1B
## 23 780 31
## [1] "Sum the counts in g2m-phase genes across 3404 cells"
## CDCA8 CDC20 KIF2C PSRC1 ANP32E CKS1B NUF2 NEK2 CENPF LBR
## 87 74 56 19 2417 629 74 21 478 4118
## CENPA BUB1 CKAP2L HJURP SMC4 ECT2 TACC3 CENPE HMGB2 CDC25C
## 31 77 70 54 2264 279 1029 121 4535 14
## HMMR TTK ANLN CDCA2 CKS2 TUBB4B CKAP5 CDK1 KIF20B KIF11
## 120 34 52 30 865 10706 1139 109 705 157
## MKI67 NCAPD2 CDCA3 CBX5 TMPO GAS2L3 CKAP2 G2E3 DLGAP5 NUSAP1
## 192 604 28 1572 3671 267 1019 1112 64 376
## CCNB2 KIF23 CTCF PIMREG AURKB TOP2A JPT1 BIRC5 NDC80 TPX2
## 140 293 2525 5 49 437 7593 126 92 190
## UBE2C AURKA RANGAP1 GTSE1
## 151 391 606 80## Picking joint bandwidth of 0.255## Picking joint bandwidth of 0.118## Picking joint bandwidth of 0.644## Picking joint bandwidth of 0.334
## [1] "Sum the counts in s-phase genes across 1873 cells"
## CLSPN NASP USP1 DTL EXO1 RRM2 MSH2 POLR1B
## 77 2022 917 28 7 14 161 136
## MCM6 CDCA7 SLBP CENPU MRPL36 GMNN CASP8AP2 RFC2
## 170 106 1167 78 879 238 599 350
## MCM7 POLA1 MCM4 CCNE2 DSCC1 ATAD2 RRM1 E2F8
## 394 133 139 233 19 390 318 9
## FEN1 POLD3 HELLS RAD51AP1 PRIM1 UNG UBR7 WDR76
## 130 547 255 62 76 55 210 102
## TIPIN BLM GINS2 CDC6 TYMS PCNA UHRF1 CDC45
## 152 200 20 23 130 451 56 10
## MCM5 CHAF1B
## 451 20
## [1] "Sum the counts in g2m-phase genes across 1873 cells"
## CDCA8 CDC20 KIF2C PSRC1 ANP32E CKS1B NUF2 NEK2 CENPF LBR
## 44 38 22 10 1058 251 30 9 235 2312
## CENPA BUB1 CKAP2L HJURP SMC4 ECT2 TACC3 CENPE HMGB2 CDC25C
## 18 36 25 15 1575 135 592 92 2018 2
## HMMR TTK ANLN CDCA2 CKS2 TUBB4B CKAP5 CDK1 KIF20B KIF11
## 44 16 26 14 331 5679 629 34 420 75
## MKI67 NCAPD2 CDCA3 CBX5 TMPO GAS2L3 CKAP2 G2E3 DLGAP5 NUSAP1
## 133 343 13 854 1850 175 492 530 21 196
## CCNB2 KIF23 CTCF PIMREG AURKB TOP2A JPT1 BIRC5 NDC80 TPX2
## 64 123 1564 3 21 219 3512 53 39 102
## UBE2C AURKA RANGAP1 GTSE1
## 56 214 328 44Save Data
If you add filtering, make sure that you adjust the file saving accordingly
## [1] "Saving preprocessed data in individual objects in aml_eto.preprocSO.nofilt.2021-01-05.rds"## R version 4.0.2 (2020-06-22)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Catalina 10.15.7
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] dplyr_1.0.2 patchwork_1.0.1 networkD3_0.4 knitr_1.30
## [5] ggplot2_3.3.2 data.table_1.13.0 Seurat_3.2.2
##
## loaded via a namespace (and not attached):
## [1] nlme_3.1-149 matrixStats_0.57.0 RcppAnnoy_0.0.16
## [4] RColorBrewer_1.1-2 httr_1.4.2 sctransform_0.3
## [7] tools_4.0.2 R6_2.4.1 irlba_2.3.3
## [10] rpart_4.1-15 KernSmooth_2.23-17 uwot_0.1.8
## [13] mgcv_1.8-33 lazyeval_0.2.2 colorspace_1.4-1
## [16] withr_2.3.0 tidyselect_1.1.0 gridExtra_2.3
## [19] compiler_4.0.2 plotly_4.9.2.1 labeling_0.3
## [22] scales_1.1.1 lmtest_0.9-38 spatstat.data_1.4-3
## [25] ggridges_0.5.2 pbapply_1.4-3 spatstat_1.64-1
## [28] goftest_1.2-2 stringr_1.4.0 digest_0.6.25
## [31] spatstat.utils_1.17-0 rmarkdown_2.4 pkgconfig_2.0.3
## [34] htmltools_0.5.0 fastmap_1.0.1 htmlwidgets_1.5.2
## [37] rlang_0.4.7 shiny_1.5.0 farver_2.0.3
## [40] generics_0.0.2 zoo_1.8-8 jsonlite_1.7.1
## [43] ica_1.0-2 magrittr_1.5 Matrix_1.2-18
## [46] Rcpp_1.0.5 munsell_0.5.0 abind_1.4-5
## [49] reticulate_1.16 lifecycle_0.2.0 stringi_1.5.3
## [52] yaml_2.2.1 MASS_7.3-53 Rtsne_0.15
## [55] plyr_1.8.6 grid_4.0.2 parallel_4.0.2
## [58] listenv_0.8.0 promises_1.1.1 ggrepel_0.8.2
## [61] crayon_1.3.4 deldir_0.1-29 miniUI_0.1.1.1
## [64] lattice_0.20-41 cowplot_1.1.0 splines_4.0.2
## [67] tensor_1.5 pillar_1.4.6 igraph_1.2.5
## [70] future.apply_1.6.0 reshape2_1.4.4 codetools_0.2-16
## [73] leiden_0.3.3 glue_1.4.2 evaluate_0.14
## [76] vctrs_0.3.4 png_0.1-7 httpuv_1.5.4
## [79] gtable_0.3.0 RANN_2.6.1 purrr_0.3.4
## [82] polyclip_1.10-0 tidyr_1.1.2 future_1.19.1
## [85] xfun_0.18 rsvd_1.0.3 mime_0.9
## [88] xtable_1.8-4 later_1.1.0.1 survival_3.2-7
## [91] viridisLite_0.3.0 tibble_3.0.3 cluster_2.1.0
## [94] globals_0.13.0 fitdistrplus_1.1-1 ellipsis_0.3.1
## [97] ROCR_1.0-11